{"id":"W4250851001","doi":"10.1115/pvp2008-61771","title":"Analysis of Variable Amplitude Fatigue Data of the P355NL1 Steel Using the Effective Strain Damage Model","year":2008,"lang":"en","type":"article","venue":"Volume 1: Codes and Standards","topic":"Fatigue and fracture mechanics","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Royal Military College of Canada","funders":"","keywords":"Amplitude; Structural engineering; Materials science; Robustness (evolution); Range (aeronautics); Paris' law; Crack closure; Mechanics; Composite material; Fracture mechanics; Physics; Engineering; Optics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006366451,0.0001360451,0.0003329376,0.00006712967,0.0001296081,0.00001859298,0.0003369439,0.00006858206,0.00001752707],"category_scores_gemma":[0.00006326101,0.00008577097,0.00007316621,0.0004859286,0.0001139778,0.0001104532,0.00011271,0.0001491357,3.87773e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005189505,"about_ca_system_score_gemma":0.00007532547,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001753988,"about_ca_topic_score_gemma":0.0001191819,"domain_scores_codex":[0.9990221,0.00005152296,0.0002273217,0.0001521707,0.0003899923,0.0001568957],"domain_scores_gemma":[0.9990157,0.0000768826,0.00005950084,0.0006730374,0.0001425307,0.00003231101],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001257113,0.00001539973,0.001714108,0.00009016131,0.000791051,9.327373e-7,0.001048103,0.9866762,0.00676974,0.0007768335,0.0005298248,0.001575063],"study_design_scores_gemma":[0.0001576153,0.00001936479,0.003208604,0.00003018274,0.0004677598,0.000001341961,0.0001320306,0.9942133,0.0008464312,0.0002036996,0.0006211521,0.00009845566],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2797121,0.0005634694,0.7131779,0.00001125308,0.00007197865,0.0001839898,0.005849743,0.00002443434,0.0004050978],"genre_scores_gemma":[0.9964771,0.0001552516,0.003262919,0.00001324769,0.00001407837,0.000003108432,0.00003711824,0.00001625823,0.00002088963],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.716765,"threshold_uncertainty_score":0.3497639,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04108588549557859,"score_gpt":0.2779997733659178,"score_spread":0.2369138878703392,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}